Monocular depth estimation, which plays a crucial role in understanding 3D scene
geometry, is an ill-posed prob-lem. Recent methods have gained significant improvement by …

Estimating depth from a single RGB images is a fundamental task in computer vision, which
is most directly solved using supervised deep learning. In the field of unsupervised learning …

Depth estimation is a fundamental task in many vision applications. With the popularity of
omnidirectional cameras, it becomes a new trend to tackle this problem in the spherical …

Self-supervised depth estimation has drawn much attention in recent years as it does not
require labeled data but image sequences. Moreover, it can be conveniently used in various …

Recovering the three-dimensional structure information from a monocular camera is
significant for automated driving, robot navigation, and traffic safety assessment. Recent …

Existing augmented reality (AR) applications often ignore the occlusion between real hands
and virtual objects when incorporating virtual objects in user's views. The challenges come …

Abstract Monocular Depth Estimation (MDE) is a task to predict a dense depth map from a
single image. Despite the recent progress brought by deep learning, existing methods are …

Depth map estimation from a single RGB image is a fundamental computer vision and
image processing task for various applications. Deep learning based depth map estimation …

Monocular depth estimation is an undirected problem, so constructing a network to predict
better image depth information is an important research topic. This paper proposes a mixed …

What can we tell from a single motion-blurred image? We show in this paper that a 3D scene
can be revealed. Unlike prior methods that focus on producing a deblurred image, we …